Urban-rural differences in the association between long-term exposure to ambient particulate matter (PM) and malnutrition status among children under five years old: A cross-sectional study in China

Background The evidence regarding the relationship between postnatal exposure of air pollution and child malnutrition indicators, as well as the corresponding urban-rural disparities, is limited, especially in low-pollution area of low- and middle-income countries (LMICs). Therefore, our aim was to contrast the effect estimates of varying ambient particulate matter (PM) on malnutrition indicators between urban and rural areas in Tibet, China. Methods Six malnutrition indicators were evaluated in this study, namely, Z-scores of height for age (HFA), Z-scores of weight for age (WFA), Z-scores of weight for height (WFH), stunting, underweight, and wasting. Exposure to particles with an aerodynamic diameter ≤2.5 micron (μm) (PM2.5), particles with an aerodynamic diameter ≤10 μm (PM10) and particles with an aerodynamic diameter between 2.5 and 10 μm (PMc) was estimated using satellite-based random forest models. Linear regression and logistic regression models were used to assess the associations between PM and the above malnutrition indicators. Furthermore, the effect estimates of different PM were contrasted between urban and rural areas. Results A total of 2511 children under five years old were included in this study. We found long-term exposure to PM2.5, PMc, and PM10 was associated with an increased risk of stunting and a decreased risk of underweight. Of these air pollutants, PMc had the strongest association for Z-scores of HFA and stunting, while PM2.5 had the strongest association for underweight. The results showed that the odds ratio (OR) for stunting were 1.36 (95% confidence interval (CI) = 1.06 to 1.75) per interquartile range (IQR) microgrammes per cubic metre (μg/m3) increase in PM2.5, 1.80 (95% CI = 1.30 to 2.50) per IQR μg/m3 increase in PMc and 1.55 (95% CI = 1.17 to 2.05) per IQR μg/m3 increase in PM10. The concentrations of PM were higher in urban areas, and the effects of PM on malnutrition indicators among urban children were higher than those of rural children. Conclusions Our results suggested that PM exposure might be an important trigger of child malnutrition. Further prospective researches are needed to provide important scientific literature for understanding child malnutrition risk concerning postnatal exposure of air pollutants and formulating synthetically social and environmental policies for malnutrition prevention.


Contents
Figure S1 Flowchart of the study population.
Table S1 Association of risk of malnutrition indicators with per 10 μg/m 3 increase of ambient air pollution in crude models.
Table S2 Association of risk of malnutrition indicators with per IQR μg/m 3 increase of ambient air pollution in crude models.
Table S3 Association between PM2.5, PMc, and PM10 and Z-scores of HFA stratified by potential modifiers.
Table S4 Association between PM2.5, PMc, and PM10 and Z-scores of WFA stratified by potential modifiers.
Table S5 Association between PM2.5, PMc, and PM10 and Z-scores of WFH stratified by potential modifiers.
Table S8 Association between PM2.5, PMc, and PM10 and wasting stratified by potential modifiers.
Table S9 Association of risk of continuous malnutrition indicators with per 10 μg/m 3 increase of ambient air pollution in different exposure times.
Table S10 Association of risk of categorical malnutrition indicators with per 10 μg/m 3 increase of ambient air pollution in different exposure times.
Table S11 Association of risk of continuous malnutrition indicators with per IQR μg/m 3 increase of ambient air pollution in different exposure times.
Table S12 Association of risk of categorical malnutrition indicators with per IQR μg/m 3 increase of ambient air pollution in different exposure times.

Figure S2
β (solid red lines) and 95%CI (dashed lines) for Z-scores of HFA with ambient air pollutant exposure.

Figure S3
β (solid red lines) and 95%CI (dashed lines) for Z-scores of WFA with ambient air pollutant exposure.Notes: Bold fonts indicates the effect was statistically significant (P<0.05).PM2.5, particulate matter with an aerodynamic diameter of 2.5 μm; PMc, particulate matter with an aerodynamic diameter of 2.5 to 10 μm, PM10 , particulate matter with an aerodynamic diameter of 10 μm.HFA, height for age; WFA, weight for age; WFH, weight for height.The models were adjusted for age, sex, low birth weight, asthma history, anemia history, history of dental caries, being ill for the last two weeks, optimal feeding scores, secondary smoke, residence, maternal education level, Maternal height, maternal weight, mother suffering from anemia during pregnancy, wealth category, drinking water source, relative humidity, mean temperature, altitude.Notes: Bold fonts indicates the effect was statistically significant (P<0.05).PM2.5, particulate matter with an aerodynamic diameter of 2.5 μm; PMc, particulate matter with an aerodynamic diameter of 2.5 to 10 μm, PM10 , particulate matter with an aerodynamic diameter of 10 μm.The models were adjusted for adjusted for age, sex, low birth weight, asthma history, anemia history, history of dental caries, being ill for the last two weeks, optimal feeding scores, secondary smoke, residence, maternal education level, Maternal height, maternal weight, mother suffering from anemia during pregnancy, wealth category, drinking water source, relative humidity, mean temperature, altitude.Stunting: Z-scores of HFA<-2.Underweight: Z-scores of WFA<-2.Wasting: Z-scores of WFA<-2.Notes: Bold fonts indicates the effect was statistically significant (P<0.05).PM2.5, particulate matter with an aerodynamic diameter of 2.5 μm; PMc, particulate matter with an aerodynamic diameter of 2.5 to 10 μm, PM10 , particulate matter with an aerodynamic diameter of 10 μm.The models were adjusted for adjusted for age, sex, low birth weight, asthma history, anemia history, history of dental caries, being ill for the last two weeks, optimal feeding scores, secondary smoke, residence, maternal education level, Maternal height, maternal weight, mother suffering from anemia during pregnancy, wealth category, drinking water source, relative humidity, mean temperature, altitude.Stunting: Z-scores of HFA<-2.Underweight: Z-scores of WFA<-2.Wasting: Z-scores of WFA<-2.

Figure S2
β (solid red lines) and 95%CI (dashed lines) for Z-scores of HFA with ambient air pollutant exposure.
Notes: HFA, height for age.The adjusted models were adjusted for age, sex, low birth weight, asthma history, anemia history, history of dental caries, being ill for the last two weeks, optimal feeding scores, secondary smoke, residence, maternal education level, Maternal height, maternal weight, mother suffering from anemia during pregnancy, wealth category, drinking water source, relative humidity, mean temperature, altitude.
Figure S3 β (solid red lines) and 95%CI (dashed lines) for Z-scores of WFA with ambient air pollutant exposure.
Notes: WFA, weight for age.The adjusted models were adjusted for age, sex, low birth weight, asthma history, anemia history, history of dental caries, being ill for the last two weeks, optimal feeding scores, secondary smoke, residence, maternal education level, Maternal height, maternal weight, mother suffering from anemia during pregnancy, wealth category, drinking water source, relative humidity, mean temperature, altitude.Notes: WFA, weight for height.The adjusted models were adjusted for age, sex, low birth weight, asthma history, anemia history, history of dental caries, being ill for the last two weeks, optimal feeding scores, secondary smoke, residence, maternal education level, Maternal height, maternal weight, mother suffering from anemia during pregnancy, wealth category, drinking water source, relative humidity, mean temperature, altitude.
Figure S5 OR (solid red lines) and 95%CI (shaded part) for stunting with ambient air pollutant exposure.
Notes: Stunting: Z-scores of HFA<-2.The adjusted models were adjusted for age, sex, low birth weight, asthma history, anemia history, history of dental caries, being ill for the last two weeks, optimal feeding scores, secondary smoke, residence, maternal education level, Maternal height, maternal weight, mother suffering from anemia during pregnancy, wealth category, drinking water source, relative humidity, mean temperature, altitude.Notes: Underweight: Z-scores of WFA<-2.The adjusted models were adjusted for age, sex, low birth weight, asthma history, anemia history, history of dental caries, being ill for the last two weeks, optimal feeding scores, secondary smoke, residence, maternal education level, Maternal height, maternal weight, mother suffering from anemia during pregnancy, wealth category, drinking water source, relative humidity, mean temperature, altitude.
Figure S7 OR (solid red lines) and 95%CI (shaded part) for wasting with ambient air pollutant exposure.
Notes: Wasting: Z-scores of WFH<-2.The adjusted models were adjusted for age, sex, low birth weight, asthma history, anemia history, history of dental caries, being ill for the last two weeks, optimal feeding scores, secondary smoke, residence, maternal education level, Maternal height, maternal weight, mother suffering from anemia during pregnancy, wealth category, drinking water source, relative humidity, mean temperature, altitude.

Figure
Figure S4β (solid red lines) and 95%CI (dashed lines) for Z-scores of WFH with ambient air pollutant exposure.

Figure
Figure S5OR (solid red lines) and 95%CI (shaded part) for stunting with ambient air pollutant exposure.

Figure
Figure S6OR (solid red lines) and 95%CI (shaded part) for underweight with ambient air pollutant exposure.

Figure
Figure S7OR (solid red lines) and 95%CI (shaded part) for wasting with ambient air pollutant exposure.

Figure S1
Figure S1Flowchart of the study population.

Figure
Figure S4 β (solid red lines) and 95%CI (dashed lines) for Z-scores of WFH with ambient air pollutant exposure.

Figure
Figure S6 OR (solid red lines) and 95%CI (shaded part) for underweight with ambient air pollutant exposure.

Table S1
Associations of risk of malnutrition indicators with per 10 μg/m 3 increase of ambient air pollution in crude models.Bold fonts indicates the effect was statistically significant (P<0.05).PM2.5, particulate matter with an aerodynamic diameter of 2.5 μm; PMc, particulate matter with an aerodynamic diameter of 2.5 to 10 μm, PM10 , particulate matter with an aerodynamic diameter of 10 μm.HFA, height for age; WFA, weight for age; WFH, weight for height. *Notes:

Table S2
Associations of risk of malnutrition indicators with per IQR μg/m 3 increase of ambient air pollution in crude models.

P value for difference β(95%CI) P value for difference Age, months
*P value for difference: Z test was used to test for statistically significant difference in β estimates across categories within subgroups.For example, in rural area vs urban area, we calculated: Z=

Table S4
Association between PM2.5, PMc, and PM10 and Z-scores of WFA stratified by potential modifiers Notes: Bold fonts indicates the effect was statistically significant (P<0.05).WFA, weight for age.The models were adjusted for age, sex, low birth weight, asthma history, anemia history, history of dental caries, being ill for the last two weeks, optimal feeding scores, secondary smoke, residence, maternal education level, Maternal height, maternal weight, mother suffering from anemia during pregnancy, wealth category, drinking water source, relative humidity, mean temperature, altitude.*Pvalue for difference: Z test was used to test for statistically significant difference in β estimates across categories within subgroups.For example, in rural area vs urban area, we calculated: Z=

Table S5
Association between PM2.5, PMc, and PM10 and Z-scores of WFH stratified by potential modifiers Notes: Bold fonts indicates the effect was statistically significant (P<0.05).WFH, weight for height.The models were adjusted for age, sex, low birth weight, asthma history, anemia history, history of dental caries, being ill for the last two weeks, optimal feeding scores, secondary smoke, residence, maternal education level, Maternal height, maternal weight, mother suffering from anemia during pregnancy, wealth category, drinking water source, relative humidity, mean temperature, altitude.*Pvaluefor difference: Z test was used to test for statistically significant difference in β estimates across categories within subgroups.For example, in rural area vs urban area, we calculated: Z= Notes: Bold fonts indicates the effect was statistically significant (P<0.05).Stunting, Z-scores of HFA ≤-2.The models were adjusted for age, sex, low birth weight, asthma history, anemia history, history of dental caries, being ill for the last two weeks, optimal feeding scores, secondary smoke, residence, maternal education level, Maternal height, maternal weight, mother suffering from anemia during pregnancy, wealth category, drinking water source, relative humidity, mean temperature, altitude.*Pvalue for difference: Z test was used to test for statistically significant difference in β estimates across categories within subgroups.For example, in rural area vs urban area, we calculated: Z=

Table S7
Association between PM2.5, PMc, and PM10 and underweight stratified by potential modifiers Notes: Bold fonts indicates the effect was statistically significant (P<0.05).Underweight, Z-scores of WFA ≤ -2.The models were adjusted for age, sex, low birth weight, asthma history, anemia history, history of dental caries, being ill for the last two weeks, optimal feeding scores, secondary smoke, residence, maternal education level, Maternal height, maternal weight, mother suffering from anemia during pregnancy, wealth category, drinking water source, relative humidity, mean temperature, altitude.*Pvaluefor difference: Z test was used to test for statistically significant difference in β estimates across categories within subgroups.For example, in rural area vs urban area, we calculated: Z= Notes: Bold fonts indicates the effect was statistically significant (P<0.05).Wasting, Z-scores of WFH ≤ -2.The models were adjusted for age, sex, low birth weight, asthma history, anemia history, history of dental caries, being ill for the last two weeks, optimal feeding scores, secondary smoke, residence, maternal education level, Maternal height, maternal weight, mother suffering from anemia during pregnancy, wealth category, drinking water source, relative humidity, mean temperature, altitude.*Pvalue for difference: Z test was used to test for statistically significant difference in β estimates across categories within subgroups.For example, in rural area vs urban area, we calculated: Z=

Table S9
Association of risk of continuous malnutrition indicators with per 10 μg/m 3 increase of ambient air pollution in different exposure times

Table S10
Association of risk of categorical malnutrition indicators with per 10-μg/m 3 increase of ambient air pollution in different exposure times

Table S11
Association of risk of continuous malnutrition indicators with per IQR μg/m 3 increase of ambient air pollution in different exposure times The models were adjusted for age, sex, low birth weight, asthma history, anemia history, history of dental caries, being ill for the last two weeks, optimal feeding scores, secondary smoke, residence, maternal education level, Maternal height, maternal weight, mother suffering from anemia during pregnancy, wealth category, drinking water source, relative humidity, mean temperature, altitude.

Table S12
Association of risk of categorical malnutrition indicators with per IQR-μg/m 3 increase of ambient air pollution in different exposure times